Day by day, human-agent negotiation becomes more and more vital to reach a socially beneficial ag... more Day by day, human-agent negotiation becomes more and more vital to reach a socially beneficial agreement when stakeholders need to make a joint decision together. Developing agents who understand not only human preferences but also attitudes is a significant prerequisite for this kind of interaction. Studies on opponent modeling are predominantly based on automated negotiation and may yield good predictions after exchanging hundreds of offers. However, this is not the case in human-agent negotiation in which the total number of rounds does not usually exceed tens. For this reason, an opponent model technique is needed to extract the maximum information gained with limited interaction. This study presents a conflict-based opponent modeling technique and compares its prediction performance with the well-known approaches in human-agent and automated negotiation experimental settings. According to the results of human-agent studies, the proposed model outpr erforms them despite the dive...
Conflict resolution is essential to obtain cooperation in many scenarios such as politics and bus... more Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science and artificial intelligence have, in turn, been inspired by theories and techniques from these disciplines, which has led to a variety of computational models and approaches, such as automated negotiation, group decision making, argumentation, preference aggregation, and human-machine interaction. To bring together the different research strands and disciplines in conflict resolution, the Workshop on Conflict Resolution in Decision Making (COREDEMA) was organized. This special issue benefited from the workshop series, and consists of significantly extended and revised selected papers from the ECAI 2016 COREDEMA workshop, as well as completely new contributions.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Journal of Systems Science and Systems Engineering, Mar 21, 2018
Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually sa... more Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A variety of automated negotiation mechanisms have been proposed in the literature. The effectiveness of those mechanisms, however, may depend on the characteristics of the underlying negotiation problem (e.g. on the complexity of participant's utility functions, as well as the degree of conflict between participants). While one mechanism may be a good choice for a negotiation problem, it may be a poor choice for another. In this paper, we pursue the problem of selecting the most effective negotiation mechanism given a particular problem by (1) defining a set of scenario metrics to capture the relevant features of negotiation problems, (2) evaluating the performance of a range of negotiation mechanisms on a diverse test suite of negotiation scenarios, (3) applying machine learning techniques to identify which mechanisms work best with which scenarios, and (4) demonstrating that using these classification rules for mechanism selection enables significantly better negotiation performance than any single mechanism alone.
Designing agents aiming to negotiate with human counterparts requires additional factors. In this... more Designing agents aiming to negotiate with human counterparts requires additional factors. In this work, we analyze the main elements of human negotiations in a structured human experiment. Particularly, we focus on studying the effect of negotiators' being aware of the other side's gain on the bidding behavior and the negotiation outcome. We compare the negotiations in two settings where one allows human negotiators to see their opponent's utility and the other does not. Furthermore, we study what kind of emotional state expressed and arguments sent in those setups. We rigorously discuss the findings from our experiments.
This paper introduces a negotiation framework to solve Multi-Agent Path Finding (MAPF) Problem fo... more This paper introduces a negotiation framework to solve Multi-Agent Path Finding (MAPF) Problem for self-interested agents in a decentralized fashion. The framework aims to achieve a good trade-off between the privacy of the agents and the effectiveness of solutions. Accordingly, a token-based bilateral negotiation protocol and two negotiation strategies are presented. The experimental results over four different settings of MAPF problem showed that the proposed approach could find conflict-free path solutions albeit suboptimally, especially when the search space is large and high-density, whereas Explicit Estimation Conflict-Based Search (EECBS) struggles to find optimal solutions. Besides, deploying a sophisticated negotiation strategy that utilizes information about local density for generating alternative paths can yield remarkably better solution performance in this negotiation framework.
While junction temperature control is an indispensable part of having reliable solid-state lighti... more While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based junction temperature measurement techniques have been used in practice. Researchers calibrate different spectral power distribution behaviors to a specific temperature and then use that to predict the junction temperature. White light in white LEDs is composed of blue chip emission and down-converted emission from photoluminescent particles, each with its own behavior at different temperatures. These two emissions can be combined in an unlimited number of ways to produce diverse white colors at different brightness levels. The shape of the spectral power distribution can, in essence, be compressed into a correlated color temperature (CCT). The intensity level of the spectral power distribution can be inferred from the luminous flux as it is the special weighted inte...
Artificial Intelligence (AI) changed our world in various ways. People start to interact with a v... more Artificial Intelligence (AI) changed our world in various ways. People start to interact with a variety of intelligent systems frequently. As the interaction between human and AI systems increases day by day, the factors influencing their communication have become more and more important, especially in the field of human-agent negotiation. In this study, our aim is to investigate the effect of knowing your negotiation partner (i.e., opponent) with limited knowledge, particularly the effect of familiarity with the opponent during human-agent negotiation so that we can design more effective negotiation systems. As far as we are aware, this is the first study investigating this research question in human-agent negotiation settings. Accordingly, we present a human-agent negotiation framework and conduct a user experiment in which participants negotiate with an avatar whose appearance and voice are a replica of a celebrity of their choice and with an avatar whose appearance and voice are...
IEEE/WIC/ACM International Conference on Web Intelligence
This study presents Bargaining Chips: a framework for one-tomany concurrent composite negotiation... more This study presents Bargaining Chips: a framework for one-tomany concurrent composite negotiations, where multiple deals can be reached and combined. Our framework is designed to mirror the salient aspects of real-life procurement and trading scenarios, in which a buyer seeks to acquire a number of items from different sellers at the same time. To do so, the buyer needs to successfully perform multiple concurrent bilateral negotiations as well as coordinate the composite outcome resulting from each interdependent negotiation. This paper contributes to the state of the art by: (1) presenting a model and test-bed for addressing such challenges; (2) by proposing a new, asynchronous interaction protocol for coordinating concurrent negotiation threads; and (3) by providing classes of multi-deal coordinators that are able to navigate this new one-to-many multi-deal setting. We show that Bargaining Chips can be used to evaluate general asynchronous negotiation and coordination strategies in a setting that generalizes over a number of existing negotiation approaches. CCS CONCEPTS • Applied computing → Electronic commerce; Multi-criterion optimization and decision-making.
Let’s Negotiate with Jennifer! Towards a Speech-Based Human-Robot Negotiation
Advances in Automated Negotiations, 2020
Social robots are becoming prevalent in our society, and most of the time, they need to interact ... more Social robots are becoming prevalent in our society, and most of the time, they need to interact with humans in order to accomplish their tasks. Negotiation is one of the inevitable processes they need to be involved to make joint decisions with their human counterparts when there is a conflict of interest between them. This paper pursues a novel approach for a humanoid robot to negotiate with humans efficiently via speech. In this work, we propose a speech-based negotiation protocol in which agents make their offers in a turn-taking fashion via speech. We present a variant of time-based concession bidding strategy for the humanoid robot and evaluated the performance of the robot against human counterpart in human-robot negotiation experiments.
Designing agents aiming to negotiate with human counterparts requires additional factors. In this... more Designing agents aiming to negotiate with human counterparts requires additional factors. In this work, we analyze the main elements of human negotiations in a structured human experiment. Particularly, we focus on studying the effect of negotiators' being aware of the other side's gain on the bidding behavior and the negotiation outcome. We compare the negotiations in two settings where one allows human negotiators to see their opponent's utility and the other does not. Furthermore, we study what kind of emotional state expressed and arguments sent in those setups. We rigorously discuss the findings from our experiments.
Conflict resolution is essential to obtain cooperation in many scenarios such as politics and bus... more Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science and artificial intelligence have, in turn, been inspired by theories and techniques from these disciplines, which has led to a variety of computational models and approaches, such as automated negotiation, group decision making, argumentation, preference aggregation, and human-machine interaction. To bring together the different research strands and disciplines in conflict resolution, the Workshop on Conflict Resolution in Decision Making (COREDEMA) was organized. This special issue benefited from the workshop series, and consists of significantly extended and revised selected papers from the ECAI 2016 COREDEMA workshop, as well as completely new ...
Journal of Reliable Intelligent Environments, 2021
This paper proposes and evaluates a new airline disruption management strategy using multi-agent ... more This paper proposes and evaluates a new airline disruption management strategy using multi-agent system modelling, simulation, and verification. This new strategy is based on a multi-agent negotiation protocol and is compared with three airline strategies based on established industry practices. The application concerns Airline Operations Control whose core functionality is disruption management. To evaluate the new strategy, a rule-based multi-agent system model of the AOC and crew processes has been developed. This model is used to assess the effects of multi-agent negotiation on airline performance in the context of a challenging disruption scenario. For the specific scenario considered, the multi-agent negotiation strategy outperforms the established strategies when the agents involved in the negotiation are experts. Another important contribution is that the paper presents a logic-based ontology used for formal modelling and analysis of AOC workflows.
Multi-Agent Systems and Agreement Technologies, 2020
The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest i... more The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. To facilitate the research on agent-based negotiation, the organizers introduce new research challenges every year. ANAC 2019 posed five negotiation challenges: automated negotiation with partial preferences, repeated human-agent negotiation, negotiation in supplychain management, negotiating in the strategic game of Diplomacy, and in the Werewolf game. This paper introduces the challenges and discusses the main findings and lessons learnt per league.
Proceedings of the 12th International Conference on Agents and Artificial Intelligence, 2020
In a supply chain environment, supply chain entities need to make joint decisions on the transact... more In a supply chain environment, supply chain entities need to make joint decisions on the transaction of goods under the issues quantity, delivery time and unit price in order to procure/sell goods at right quantities and time while minimizing the transaction costs. This paper presents our negotiating agent designed for Supply Chain Management League (SCML) in the International Automated Negotiation Agents Competition (ANAC). Basically, the proposed approach relies on determining reservation value by taking the changes in the inventory stock into account. We have tested the performance of our bidding strategy in the competition simulation environment and compared it with the performance of the winner strategies in ANAC SCML 2019. Our experimental results showed that the proposed strategy outperformed the winner strategies in overall.
The game of Diplomacy has been used as a test case for complex automated negotiations for a long ... more The game of Diplomacy has been used as a test case for complex automated negotiations for a long time, but to date very few successful negotiation algorithms have been implemented for this game. We have therefore decided to include a Diplomacy tournament within the annual Automated Negotiating Agents Competition (ANAC). In this paper we present the setup and the results of the ANAC 2017 Diplomacy Competition and the ANAC 2018 Diplomacy Challenge. We observe that none of the negotiation algorithms submitted to these two editions have been able to significantly improve the performance over a non-negotiating baseline agent. We analyze these algorithms and discuss why it is so hard to write successful negotiation algorithms for Diplomacy. Finally, we provide experimental evidence that, despite these results, coalition formation and coordination do form essential elements of the game.
Deep learning can be used to automate aircraft maintenance visual inspection. This can help incre... more Deep learning can be used to automate aircraft maintenance visual inspection. This can help increase the accuracy of damage detection, reduce aircraft downtime, and help prevent inspection accidents. The objective of this paper is to demonstrate the potential of this method in supporting aircraft engineers to automatically detect aircraft dents. The novelty of the work lies in applying a recently developed neural network architecture know by Mask R-CNN, which enables the detection of objects in an image while simultaneously generating a segmentation mask for each instance. Despite the small dataset size used for training, the results are promising and demonstrate the potential of deep learning to automate aircraft maintenance inspection. The model can be trained to identify additional types of damage such as lightning strike entry and exit points, paint damage, cracks and holes, missing markings, and can therefore be a useful decision-support system for aircraft engineers.
Day by day, human-agent negotiation becomes more and more vital to reach a socially beneficial ag... more Day by day, human-agent negotiation becomes more and more vital to reach a socially beneficial agreement when stakeholders need to make a joint decision together. Developing agents who understand not only human preferences but also attitudes is a significant prerequisite for this kind of interaction. Studies on opponent modeling are predominantly based on automated negotiation and may yield good predictions after exchanging hundreds of offers. However, this is not the case in human-agent negotiation in which the total number of rounds does not usually exceed tens. For this reason, an opponent model technique is needed to extract the maximum information gained with limited interaction. This study presents a conflict-based opponent modeling technique and compares its prediction performance with the well-known approaches in human-agent and automated negotiation experimental settings. According to the results of human-agent studies, the proposed model outpr erforms them despite the dive...
Conflict resolution is essential to obtain cooperation in many scenarios such as politics and bus... more Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science and artificial intelligence have, in turn, been inspired by theories and techniques from these disciplines, which has led to a variety of computational models and approaches, such as automated negotiation, group decision making, argumentation, preference aggregation, and human-machine interaction. To bring together the different research strands and disciplines in conflict resolution, the Workshop on Conflict Resolution in Decision Making (COREDEMA) was organized. This special issue benefited from the workshop series, and consists of significantly extended and revised selected papers from the ECAI 2016 COREDEMA workshop, as well as completely new contributions.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Journal of Systems Science and Systems Engineering, Mar 21, 2018
Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually sa... more Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A variety of automated negotiation mechanisms have been proposed in the literature. The effectiveness of those mechanisms, however, may depend on the characteristics of the underlying negotiation problem (e.g. on the complexity of participant's utility functions, as well as the degree of conflict between participants). While one mechanism may be a good choice for a negotiation problem, it may be a poor choice for another. In this paper, we pursue the problem of selecting the most effective negotiation mechanism given a particular problem by (1) defining a set of scenario metrics to capture the relevant features of negotiation problems, (2) evaluating the performance of a range of negotiation mechanisms on a diverse test suite of negotiation scenarios, (3) applying machine learning techniques to identify which mechanisms work best with which scenarios, and (4) demonstrating that using these classification rules for mechanism selection enables significantly better negotiation performance than any single mechanism alone.
Designing agents aiming to negotiate with human counterparts requires additional factors. In this... more Designing agents aiming to negotiate with human counterparts requires additional factors. In this work, we analyze the main elements of human negotiations in a structured human experiment. Particularly, we focus on studying the effect of negotiators' being aware of the other side's gain on the bidding behavior and the negotiation outcome. We compare the negotiations in two settings where one allows human negotiators to see their opponent's utility and the other does not. Furthermore, we study what kind of emotional state expressed and arguments sent in those setups. We rigorously discuss the findings from our experiments.
This paper introduces a negotiation framework to solve Multi-Agent Path Finding (MAPF) Problem fo... more This paper introduces a negotiation framework to solve Multi-Agent Path Finding (MAPF) Problem for self-interested agents in a decentralized fashion. The framework aims to achieve a good trade-off between the privacy of the agents and the effectiveness of solutions. Accordingly, a token-based bilateral negotiation protocol and two negotiation strategies are presented. The experimental results over four different settings of MAPF problem showed that the proposed approach could find conflict-free path solutions albeit suboptimally, especially when the search space is large and high-density, whereas Explicit Estimation Conflict-Based Search (EECBS) struggles to find optimal solutions. Besides, deploying a sophisticated negotiation strategy that utilizes information about local density for generating alternative paths can yield remarkably better solution performance in this negotiation framework.
While junction temperature control is an indispensable part of having reliable solid-state lighti... more While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based junction temperature measurement techniques have been used in practice. Researchers calibrate different spectral power distribution behaviors to a specific temperature and then use that to predict the junction temperature. White light in white LEDs is composed of blue chip emission and down-converted emission from photoluminescent particles, each with its own behavior at different temperatures. These two emissions can be combined in an unlimited number of ways to produce diverse white colors at different brightness levels. The shape of the spectral power distribution can, in essence, be compressed into a correlated color temperature (CCT). The intensity level of the spectral power distribution can be inferred from the luminous flux as it is the special weighted inte...
Artificial Intelligence (AI) changed our world in various ways. People start to interact with a v... more Artificial Intelligence (AI) changed our world in various ways. People start to interact with a variety of intelligent systems frequently. As the interaction between human and AI systems increases day by day, the factors influencing their communication have become more and more important, especially in the field of human-agent negotiation. In this study, our aim is to investigate the effect of knowing your negotiation partner (i.e., opponent) with limited knowledge, particularly the effect of familiarity with the opponent during human-agent negotiation so that we can design more effective negotiation systems. As far as we are aware, this is the first study investigating this research question in human-agent negotiation settings. Accordingly, we present a human-agent negotiation framework and conduct a user experiment in which participants negotiate with an avatar whose appearance and voice are a replica of a celebrity of their choice and with an avatar whose appearance and voice are...
IEEE/WIC/ACM International Conference on Web Intelligence
This study presents Bargaining Chips: a framework for one-tomany concurrent composite negotiation... more This study presents Bargaining Chips: a framework for one-tomany concurrent composite negotiations, where multiple deals can be reached and combined. Our framework is designed to mirror the salient aspects of real-life procurement and trading scenarios, in which a buyer seeks to acquire a number of items from different sellers at the same time. To do so, the buyer needs to successfully perform multiple concurrent bilateral negotiations as well as coordinate the composite outcome resulting from each interdependent negotiation. This paper contributes to the state of the art by: (1) presenting a model and test-bed for addressing such challenges; (2) by proposing a new, asynchronous interaction protocol for coordinating concurrent negotiation threads; and (3) by providing classes of multi-deal coordinators that are able to navigate this new one-to-many multi-deal setting. We show that Bargaining Chips can be used to evaluate general asynchronous negotiation and coordination strategies in a setting that generalizes over a number of existing negotiation approaches. CCS CONCEPTS • Applied computing → Electronic commerce; Multi-criterion optimization and decision-making.
Let’s Negotiate with Jennifer! Towards a Speech-Based Human-Robot Negotiation
Advances in Automated Negotiations, 2020
Social robots are becoming prevalent in our society, and most of the time, they need to interact ... more Social robots are becoming prevalent in our society, and most of the time, they need to interact with humans in order to accomplish their tasks. Negotiation is one of the inevitable processes they need to be involved to make joint decisions with their human counterparts when there is a conflict of interest between them. This paper pursues a novel approach for a humanoid robot to negotiate with humans efficiently via speech. In this work, we propose a speech-based negotiation protocol in which agents make their offers in a turn-taking fashion via speech. We present a variant of time-based concession bidding strategy for the humanoid robot and evaluated the performance of the robot against human counterpart in human-robot negotiation experiments.
Designing agents aiming to negotiate with human counterparts requires additional factors. In this... more Designing agents aiming to negotiate with human counterparts requires additional factors. In this work, we analyze the main elements of human negotiations in a structured human experiment. Particularly, we focus on studying the effect of negotiators' being aware of the other side's gain on the bidding behavior and the negotiation outcome. We compare the negotiations in two settings where one allows human negotiators to see their opponent's utility and the other does not. Furthermore, we study what kind of emotional state expressed and arguments sent in those setups. We rigorously discuss the findings from our experiments.
Conflict resolution is essential to obtain cooperation in many scenarios such as politics and bus... more Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science and artificial intelligence have, in turn, been inspired by theories and techniques from these disciplines, which has led to a variety of computational models and approaches, such as automated negotiation, group decision making, argumentation, preference aggregation, and human-machine interaction. To bring together the different research strands and disciplines in conflict resolution, the Workshop on Conflict Resolution in Decision Making (COREDEMA) was organized. This special issue benefited from the workshop series, and consists of significantly extended and revised selected papers from the ECAI 2016 COREDEMA workshop, as well as completely new ...
Journal of Reliable Intelligent Environments, 2021
This paper proposes and evaluates a new airline disruption management strategy using multi-agent ... more This paper proposes and evaluates a new airline disruption management strategy using multi-agent system modelling, simulation, and verification. This new strategy is based on a multi-agent negotiation protocol and is compared with three airline strategies based on established industry practices. The application concerns Airline Operations Control whose core functionality is disruption management. To evaluate the new strategy, a rule-based multi-agent system model of the AOC and crew processes has been developed. This model is used to assess the effects of multi-agent negotiation on airline performance in the context of a challenging disruption scenario. For the specific scenario considered, the multi-agent negotiation strategy outperforms the established strategies when the agents involved in the negotiation are experts. Another important contribution is that the paper presents a logic-based ontology used for formal modelling and analysis of AOC workflows.
Multi-Agent Systems and Agreement Technologies, 2020
The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest i... more The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. To facilitate the research on agent-based negotiation, the organizers introduce new research challenges every year. ANAC 2019 posed five negotiation challenges: automated negotiation with partial preferences, repeated human-agent negotiation, negotiation in supplychain management, negotiating in the strategic game of Diplomacy, and in the Werewolf game. This paper introduces the challenges and discusses the main findings and lessons learnt per league.
Proceedings of the 12th International Conference on Agents and Artificial Intelligence, 2020
In a supply chain environment, supply chain entities need to make joint decisions on the transact... more In a supply chain environment, supply chain entities need to make joint decisions on the transaction of goods under the issues quantity, delivery time and unit price in order to procure/sell goods at right quantities and time while minimizing the transaction costs. This paper presents our negotiating agent designed for Supply Chain Management League (SCML) in the International Automated Negotiation Agents Competition (ANAC). Basically, the proposed approach relies on determining reservation value by taking the changes in the inventory stock into account. We have tested the performance of our bidding strategy in the competition simulation environment and compared it with the performance of the winner strategies in ANAC SCML 2019. Our experimental results showed that the proposed strategy outperformed the winner strategies in overall.
The game of Diplomacy has been used as a test case for complex automated negotiations for a long ... more The game of Diplomacy has been used as a test case for complex automated negotiations for a long time, but to date very few successful negotiation algorithms have been implemented for this game. We have therefore decided to include a Diplomacy tournament within the annual Automated Negotiating Agents Competition (ANAC). In this paper we present the setup and the results of the ANAC 2017 Diplomacy Competition and the ANAC 2018 Diplomacy Challenge. We observe that none of the negotiation algorithms submitted to these two editions have been able to significantly improve the performance over a non-negotiating baseline agent. We analyze these algorithms and discuss why it is so hard to write successful negotiation algorithms for Diplomacy. Finally, we provide experimental evidence that, despite these results, coalition formation and coordination do form essential elements of the game.
Deep learning can be used to automate aircraft maintenance visual inspection. This can help incre... more Deep learning can be used to automate aircraft maintenance visual inspection. This can help increase the accuracy of damage detection, reduce aircraft downtime, and help prevent inspection accidents. The objective of this paper is to demonstrate the potential of this method in supporting aircraft engineers to automatically detect aircraft dents. The novelty of the work lies in applying a recently developed neural network architecture know by Mask R-CNN, which enables the detection of objects in an image while simultaneously generating a segmentation mask for each instance. Despite the small dataset size used for training, the results are promising and demonstrate the potential of deep learning to automate aircraft maintenance inspection. The model can be trained to identify additional types of damage such as lightning strike entry and exit points, paint damage, cracks and holes, missing markings, and can therefore be a useful decision-support system for aircraft engineers.
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